BackgroundLine‐field confocal optical coherence tomography (LC‐OCT) is an imaging technique providing “optical biopsies” of the skin in real time and non‐invasively. At a center optical wavelength of 1.3 µm, this innovative technology can be applied to dermo‐cosmetic product development due to both high image resolution (~2 µm) and sufficient penetration (~0.5 mm). Nevertheless, the precise dermal area analyzed with LC‐OCT has never been identified. In this study, the objective was to compare LC‐OCT images with histological sections of the same area, in order to validate a new method for in vivo and non‐invasive quantification of superficial dermis thickness. Once validated, this standardized and quantitative method was used to assess age‐related changes of the superficial dermis.Materials and MethodsEx vivo LC‐OCT acquisitions and hematoxylin‐eosin‐safran staining were performed on a panel of four healthy Caucasian female volunteers. In vivo LC‐OCT study of skin aging was performed on a panel of 37 healthy Caucasian female divided into five different age‐groups.ResultsComparison with histological sections revealed that LC‐OCT images allow the visualization and the quantification of the superficial portion of papillary dermis. Applied to different age‐group of volunteers, LC‐OCT images show a constant decrease in this superficial dermis thickness with age.ConclusionsIn conclusion, we have introduced LC‐OCT as a novel technique for in vivo and non‐invasive evaluation of superficial dermis thickness. This approach could be used in the future to demonstrate visually and quantitatively the capacity of a dermo‐cosmetic active ingredient to renormalize the structural properties of the dermis.

Epidermal three-dimensional (3D) topography/quantification has not been completely characterized yet. The recently developed line-field confocal optical coherence tomography (LC-OCT) provides real-time, high-resolution, in-vivo 3D imaging of the skin. This pilot study aimed at quantifying epidermal metrics (epidermal thicknesses, dermal-epidermal junction [DEJ] undulation and keratinocyte number/shape/size) using 3D LC-OCT. For each study participant (8 female, skintype-II, younger/older volunteers), seven body sites were imaged with LC-OCT. Epidermal metrics were calculated by segmentations and measurements assisted by artificial intelligence (AI) when appropriate. Thicknesses of epidermis/SC, DEJ undulation and keratinocyte nuclei volume varied across body sites. Evidence of keratinocyte maturation was observed in vivo: keratinocyte nuclei being small/spherical near the DEJ and flatter/elliptical near the skin surface. Skin microanatomy can be quantified by combining LC-OCT and AI.This technology could be highly relevant to understand aging processes and conditions linked to epidermal disorders. Future clinical/research applications are to be expected in this scenario.

How does the concerted activity of neuronal populations shape behavior? impediments to address this question are primarily due to critical experimental barriers. An integrated perspective on large scale neural information processing requires an in vivo approach that can combine the advantages of exhaustively observing all neurons dedicated to a given type of stimulus, and simultaneously achieve a resolution that is precise enough to capture individual neuron activity. current experimental data from in vivo observations are either restricted to a small fraction of the total number of neurons, or are based on larger brain volumes but at a low spatial and temporal resolution. Consequently, fundamental questions as to how sensory information is represented on a population scale remain unanswered. in Drosophila melanogaster, the mushroom body (MB) represents an excellent model to analyze sensory coding and memory plasticity. In this work, we present an experimental setup coupled with a dedicated computational method that provides in vivo measurements of the activity of hundreds of densely packed somata uniformly spread in the MB. We exploit spinning-disk confocal 3D imaging over time of the whole MB cell body layer in vivo while it is exposed to olfactory stimulation. Importantly, to derive individual signal from densely packed somata, we have developed a fully automated image analysis procedure that takes advantage of the specificities of our data. After anisotropy correction, our approach operates a dedicated spot detection and registration over the entire time sequence to transform trajectories to identifiable clusters. This enabled us to discard spurious detections and reconstruct missing ones in a robust way. We demonstrate that this approach outperformed existing methods in this specific context and made possible high-throughput analysis of approximately 500 single somata uniformly spread over the MB in various conditions. Applying this approach, we find that learned experiences change the population code of odor representations in the MB. After long-term memory (LTM) formation, we quantified an increase in responsive somata count and a stable single neuron signal. We predict that this method, which should further enable studying the population pattern of neuronal activity, has the potential to uncover fine details of sensory processing and memory plasticity.All behavior relies on accurate information processing of sensory signals carried out by the concerted activity of populations of neurons 1,2 . While much is known about the pathways of neuronal transduction, how the integration of information derives from the cooperative action of neuronal activity remains largely elusive. However, for many functions of the brain such as sensory processing or memory plasticity, the important coding might be represented within the neuronal population rather than the individual cell. In animal models, recent developments in the field of in vivo imaging tools have allowed neuroscientists to characterize neuronal activity patte...

Disulfide bonds (S-S) play a central role in stabilizing the native structure of proteins against denaturation. Experimentally, identification of these linkages in peptide and protein structure characterization remains challenging. UV photodissociation (UVPD) can be a valuable tool in identifying disulfide linkages. Here, the S-S bond acts as a UV chromophore and absorption of one UV photon corresponds to a σ-σ* transition. We have investigated the photodissociation dynamics of protonated cystine, which is a dimer of two cysteines linked by a disulfide bridge, at 263 nm (4.7 eV) using a multicoincidence technique in which fragments coming from the same fragmentation event are detected. Two types of bond cleavages are observed corresponding to the disulfide (S-S) and adjacent C-S bond ruptures. We show that the S-S cleavage leads to three different fragment ions via three different fragmentation mechanisms. The UVPD results are compared to collision-induced dissociation (CID) and electron-induced dissociation (EID) studies.